The present invention relates to an echo canceller using an FIR filter and, more particularly, to an echo canceller which increases the converging speed of an FIR filter.
A typical application of an echo canceller is to a hybrid transformer which implements the 2-wire/4-wire conversion of a telephone line or satellite communication line and generates an echo due to impedance mismatching between the 2-wire path and the 4-wire path. Another typical application is to a TV conference system or a voice conference system in which a loudspeaker and a microphone are acoustically coupled to generate an echo. In an echo canceller, an FIR filter estimates the impulse response of an echo path from a received input signal and then generates an estimated echo signal. The estimation of an impulse response requires multiplication and addition steps to be repeated a number of times within a short period of time. The number of such arithmetic operations increases with the duration of the impulse response. For example, the multiplication and addition steps have to be repeated several hundred times within about 100 milliseconds in the case of the estimation of an echo ascribable to the hybrid transformer of a telephone line or even several thousand times when it comes to the estimation of an echo ascribable to the turn-around of a speaker output to a microphone. To promote efficient echo estimation, there have been proposed various kinds of methods such as a normalized LMS (Least Mean Square) method and an RLS (Recursive Least Square) method.
The normalized LMS method may be denoted as follows: EQU y(j)=H(j).sup.t X(j) (1) EQU e(j)=y(j)-y(j) (2) EQU H(j+1)=H(j)+.alpha.e(j)X(j)/(X(j).sup.t X(j) (3)
where y(j), y(j), e(j) and x(j) are respectively the estimated echo signal, transmission input signal, transmission output signal (difference output signal), difference between y(k) and y(k)) and received input signal at a particular time j.
A received input vector X(j) and an estimated impulse response vector H(j) at a time j are defined as: EQU X(j)=[x(j), x(j-1), . . . , x(j-N+1)].sup.t EQU H(j)=[h0(j), h1(j), . . . , hN-1(j)].sup.t
where hi(j) is the estimated impulse response at a tap position i and at a time j. Further, .alpha. is a constant which is greater than zero and smaller than 2; the converging speed is highest when .alpha. is 1.
An echo canceller of the type which estimates an echo by the normalized LMS method is disclosed by, for example, YING G. TAO in "A Cascadable VLSI Echo Canceller", IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. SAC-2, March 1984, pp. 297-303. Since the normalized LMS method is based on a statistical procedure, convergence occurs most rapidly with an input signal having no correlation, i.e., white noise. The maximum converging speed depends on the estimation order of the filter, and the convergence is completed after a number of repetitions which is about twenty times as great as the estimation order (about 30 dB in terms of the amount of echo cancellation). Assuming an acoustic echo canceller, the estimation order (number of taps) of the filter should be at least about 2,000 even when the sampling frequency is as high as 8 kilohertz, i.e., even then, more than five seconds is necessary for convergence. It follows that when the initial convergence of the path is changed, the echo is noticeably increased, which degrades the conversation quality in the communication system.
In light of the above, an echo canceller using the RLS method has also been proposed, which solves simultaneous equations to thereby produce an impulse response sequence H(j) uniformly. However, the RLS method is not practicable since it requires a prohibitive number of arithmetic operations, although it promotes rapid convergence and copes with changes of the initial convergence and path change, by comparison with the normalized LMS method.